1. Field
Example embodiments of the following disclosure relate to an apparatus and method for detecting a plane model from space information about an object, and more particularly, to an apparatus and method for detecting a plane model associated with an object from a three-dimensional (3D) point cloud associated with the object or a depth image captured from the object.
2. Description of the Related Art
Recently, an interest with respect to modeling of a three-dimensional (3D) space and applications of the modeled 3D space has been increasing. As an example, a method of decomposing a complex space based on a basic primitive may be employed.
For example, an indoor space generally includes planes, such as, walls, ceiling, floor, a desk, and the like. Therefore, a method of detecting and utilizing a plurality of planes present in the space may be efficiently employed in the modeling of the 3D space.
As the related art, a random sample consensus (RANSAC) method has been proposed. The RANSAC method may be employed as a general framework to estimate a model capable of describing observed 3D space data and may also be employed to estimate a plane in a depth image.
The above RANSAC method may estimate a plane model by randomly selecting a minimum number of points required for model estimation, for example, three points in the case of a plane, and may determine that the estimated plane model is a final plane model when the number of points supported by the estimated plane model is greater than or equal to a predetermined threshold.
However, the RANSAC method may be valid when a plane exists within a 3D space that includes a single plane instead of a plurality of planes. Further, the RANSAC method may be invalid in a plane model of the 3D space that includes a plurality of planes.
Other variation methods of estimating a plurality of planes, for example, a sequential RANSAC method, a multi-RANSAC method, and the like, have been introduced, however, may not provide the optimal solution or may require a user to pre-designate the number of planes. In particular, the variation methods may be unreliable in terms of 3D information in which noise exists.
Therefore, there is a need for an improved method and apparatus for plane detection.